Organizations and Autonomous Agents: Bottom-Up Dynamics of Coordination Mechanisms

This chapter discusses how autonomous agents can adopt organizational rules into their reasoning process. Agents in an organization need to coordinate their actions in order to reach the organizational goals. Organizational models specify the desired behaviour in terms of roles, relations, norms, and interactions. We have developed a method to translate norms into event-processing rules of the agents. We propose a modular reasoning model that includes the organizational rules explicitly. Since the agents are autonomous, they will have their own reasoning rules next to the organizational rules. The modular approach allows for meta-reasoning about these rules. We show that this stimulates bottom-up dynamics in the organization.

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Object-oriented BeNet programming for data-focused bottom-up design of autonomous agents

Robotics and Autonomous Systems ◽

10.1016/s0921-8890(99)00011-1 ◽

1999 ◽

Vol 28 (2-3) ◽

pp. 127-139 ◽

Cited By ~ 4

Author(s):

Tetsushi Oka ◽

Junya Tashiro ◽

Kunikatsu Takase

Keyword(s):

Autonomous Agents ◽

Object Oriented ◽

Bottom Up

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Bottom-Up Approach to Establish Coordination Mechanisms for Disaster Preparedness Among Largely Private Health-Care Providers in Central Tokyo

Disaster Medicine and Public Health Preparedness ◽

10.1017/dmp.2021.326 ◽

2021 ◽

pp. 1-9

Author(s):

Keyword(s):

Health Care ◽

Medical Care ◽

Disaster Preparedness ◽

Health Care Systems ◽

Health Care Personnel ◽

Coordination Mechanisms ◽

Care Providers ◽

Bottom Up ◽

Care Systems ◽

The City

Abstract In Japan, despite its private-dominant and disjointed health-care system, national initiatives to coordinate various types of health-care facilities are lacking. Municipal governments manage this task with limited resources. This study describes a successful example of a bottom-up approach to create city-wide collaboration for disaster preparedness. In Minato City, located in central Tokyo, a group of physicians created a project involving a city-wide disaster medical care drill. The city Public Health Center, in charge of health-care systems including disaster medicine, helped the group to increase proponents of the project. The city-wide disaster drill started in November 2017; thereafter, the drills were held every year. Participation in drills by various health-care personnel helped establish a city-wide system for disaster medical care, coordination mechanisms among stakeholders, increased motivation among health-care personnel, and development of in-hospital systems. This approach is flexible and applicable to various forms of health-care systems in other areas.

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Aspects of Openness in Multi-Agent Systems

Intelligence Integration in Distributed Knowledge Management ◽

10.4018/978-1-59904-576-4.ch007 ◽

2011 ◽

pp. 119-131 ◽

Cited By ~ 2

Author(s):

Marcos De Oliveira ◽

Martin Purvis

Keyword(s):

Autonomous Agents ◽

Institutional Environment ◽

Coordination Mechanisms ◽

Coloured Petri Nets ◽

Multi Agent Systems ◽

Agent Systems ◽

Agent Societies ◽

Agent Interactions ◽

Complex Agent ◽

Multi Agent

In the distributed multi-agent systems discussed in this chapter, heterogeneous autonomous agents interoperate in order to achieve their goals. In such environments, agents can be embedded in diverse contexts and interact with agents of various types and behaviours. Mechanisms are needed for coordinating these multi-agent interactions, and so far they have included tools for the support of conversation protocols and tools for the establishment and management of agent groups and electronic institutions. In this chapter, we explore the necessity of dealing with openness in multi-agent systems and its relation with the agent’s autonomy. We stress the importance to build coordination mechanisms capable of managing complex agent societies composed by autonomous agents and introduce our institutional environment approach, which includes the use of commitments and normative spaces. It is based on a metaphor in which agents may join an open system at any time, but they must obey regulations in order to maintain a suitable reputation, that reflects its degree of cooperation with other agents in the group, and make them a more desired partner for others. Coloured Petri Nets are used to formalize a workflow in the institutional environment defining a normative space that guides the agents during interactions in the conversation space.

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Multilevel Coordination Mechanisms for Real-Time Autonomous Agents

10.21236/ada421748 ◽

2004 ◽

Author(s):

Edmund H. Durfee

Keyword(s):

Real Time ◽

Autonomous Agents ◽

Coordination Mechanisms ◽

Time Autonomous

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Designing Emotions for Activity Selection

DAIMI Report Series ◽

10.7146/dpb.v29i545.7079 ◽

2000 ◽

Vol 29 (545) ◽

Cited By ~ 6

Author(s):

Dolores Canamero

Keyword(s):

Design Process ◽

Autonomous Agents ◽

Action Selection ◽

Selection Task ◽

Internal Environment ◽

Agent Architecture ◽

Bottom Up ◽

Concrete Realization ◽

Emotional System ◽

Emotional Systems

This paper advocates a ``bottom-up'' philosophy for the design of emotional systems for autonomous agents that is guided by functional concerns, and considers the particular case of designing emotions as mechanisms for action selection. The concrete realization of these ideas implies that the design process must start with an analysis of the requirements that the features of the environment, the characteristics of the action-selection task, and the agent architecture impose on the emotional system. This is particularly important if we see emotions as mechanisms that aim at modifying or maintaining the relation of the agent with its (external and internal) environment (rather than modifying the environment itself) in order to preserve the agent's goals. Emotions can then be selected and designed according to the roles they play with respect to this relation.

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Adaptive Behavior in Autonomous Agents

Presence Teleoperators & Virtual Environments ◽

10.1162/105474698565947 ◽

1998 ◽

Vol 7 (6) ◽

pp. 564-587 ◽

Cited By ~ 21

Author(s):

Tom Ziemke

Keyword(s):

Artificial Intelligence ◽

Adaptive Behavior ◽

Intelligent Agents ◽

Autonomous Agents ◽

Traditional Approach ◽

Complex Behavior ◽

Bottom Up ◽

Knowledge Based ◽

Oriented Approach

This paper provides an overview of the bottom-up approach to artificial intelligence (AI), commonly referred to as behavior-oriented AI. The behavior-oriented approach, with its focus on the interaction between autonomous agents and their environments, is introduced by contrasting it with the traditional approach of knowledge-based AI. Different notions of autonomy are discussed, and key problems of generating adaptive and complex behavior are identified. A number of techniques for the generation of behavior are introduced and evaluated regarding their potential for realizing different aspects of autonomy as well as adaptivity and complexity of behavior. It is concluded that, in order to realize truly autonomous and intelligent agents, the behavior-oriented approach will have to focus even more on lifelike qualities in both agents and environments.

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